HPCC: High Precision Congestion Control

Yuliang Li (Harvard University and Alibaba Group), Rui Miao, Hongqiang Liu, Yan Zhuang, Fei Feng, Lingbo Tang, Zheng Cao, Ming Zhang (Alibaba Group), Frank Kelly (University of Cambridge), Mohammad Alizadeh (MIT), Minlan Yu (Harvard University)
SIGCOMM, 2019,
Proceedings of the ACM Special Interest Group on Data Communication, 44-58.


Congestion control (CC) is the key to achieving ultra-low latency, high bandwidth and network stability in high-speed networks. From years of experience operating large scale and high-speed RDMA networks, we find the existing high-speed CC schemes have inherent limitations for reaching these goals. In this paper, we present HPCC (High Precision Congestion Control), a new high-speed CC mechanism which achieves the three goals simultaneously. HPCC leverages in-network telemetry (INT) to obtain precise link load information and controls traffic precisely. By addressing challenges such as delayed INT information during congestion and overreaction to INT information, HPCC can quickly converge to utilize free bandwidth while avoiding congestion, and can maintain near-zero in-network queues for ultra-low latency. HPCC is also fair and easy to deploy in hardware. We implement HPCC with commodity programmable NICs and switches. In our evaluation, compared to DCQCN and TIMELY, HPCC shortens flow completion time by up to 95%, causing little congestion even under large-scale incasts.


Slides and presentation available at SIGCOMM, 2019

See also Predictable vFabric on Informative Data Plane